Markdown Pricing Research Articles

Intertemporal Pricing with Strategic Customer Behavior

This paper develops a model of dynamic pricing with endogenous intertemporal demand. In the model, there is a monopolist who sells a finite inventory over a finite time horizon. The seller adjusts prices dynamically to maximize revenue. Customers arrive continually over the duration of the selling season. At each point in time, customers may purchase the product at current prices, remain in the market at a cost to purchase later, or exit, and they wish to maximize individual utility. The customer population is heterogeneous along two dimensions: they may have different valuations for the product and different degrees of patience (waiting costs).We demonstrate that heterogeneity in both valuation and patience is important because they jointly determine the structure of optimal pricing policies. In particular, when high-value customers are proportionately less patient, markdown pricing policies are effective because the high-value customers would buy early at high prices while the low-value customers are willing to wait (i.e., they are not lost). On the other hand, when the high-value customers are more patient than the low-value customers, prices should increase over time to discourage inefficient waiting. Contrary to intuition, we find that strategic waiting by customers may sometimes benefit the seller: when low-value customers wait, they compete for availability with high-value customers and thus increase their willingness to pay. Our results also shed light on how the composition of the customer population affects optimal revenue, consumer surplus, and social welfare. Finally, we consider the long-run problem of selecting the optimal initial stocking quantity.

Inter-temporal Pricing with Strategic Customer Behavior

This paper develops a model of dynamic pricing with endogenous inter-temporal demand. In the model, there is a monopolist who sells a finite inventory over a finite time horizon. The seller adjusts prices dynamically in order to maximize revenue. Customers arrive continually over the duration of the selling season. At each point in time, customers may purchase the product at current prices, remain in the market at a cost in order to purchase later, or exit, and they wish to maximize individual utility. The customer population is heterogeneous along two dimensions: they may have different valuations for the product and different degrees of patience (waiting costs). We demonstrate that heterogeneity in both valuation and patience is important because they jointly determine the structure of optimal pricing policies. In particular, when high-value customers are proportionately less patient, markdown pricing policies are effective because the high-value customers would buy early at high prices while the low-value customers are willing to wait (i.e. they are not lost). On the other hand, when the high-value customers are more patient than the low-value customers, prices should increase over time in order to discourage inefficient waiting. Contrary to intuition, we find that strategic waiting by customers may sometimes benefit the seller: when low-value customers wait, they compete for availability with high-value customers and thus increase their willingness to pay. Our results also shed light on how the composition of the customer population affects optimal revenue, consumer surplus, and social welfare. Finally, we consider the long run problem of selecting the optimal initial stocking quantity.

An encompassing view on markdown pricing strategies: an analysis of the Austrian mobile phone market

Fierce competition and rapid technological progress have considerably reduced the life cycle length for mobile phones in the last decade. Once a new mobile phone is launched, providers on the market under consideration practice a markdown strategy. Profits of the providers are generated mainly via the monthly (base plus variable) fees accruing during contract duration whereas the mobile phones are over large parts of their life cycle sold below the constant purchase price charged by the OEM supplier. The problem of applying such markdown strategies has recently been further emphasized by an increased competition among the providers cutting back revenues generated by the contracts. Although providers frequently complain about this situation of pre- and cross financing the mobile phones, none of them has yet risked stopping the practiced markdown pricing strategies. In our contribution, we investigate a new model for the analysis of the effects of alternative (markdown) pricing strategies. Building on previous research that has investigated the dynamics and feedbacks between pricing and inventory decisions caused by delays and inaccurate forecasts, we develop a more encompassing view on the market considering the dependency and dynamics between customer satisfaction, loyalty, and repeat purchase rates. Furthermore, we explicitly model price and reference price effects and their impact on the attraction of new customers. Various data sources are employed to calibrate a system dynamics model for one of the providers and its interrelation with a typical supplier and the customers. Our model indicates that a reduction of the currently practiced markdown strategy would reduce the provider’s overall profit for contract customers. In contrast, the results for prepaid customers could be improved by a careful reduction of markdowns.

Mark-down pricing: An empirical analysis of policies and revenue potential at one apparel retailer

The results of an analysis of sales and price data from a speciality retailer of women's apparel are reported. The data set contains 184 styles sold during the Spring 1993 season. A demand model similar to those in the existing literature is hypothesised, fit to the data, and then analysed to obtain estimates of revenues under various pricing policies. Both full information and adaptive policies are considered. The optimal prices suggested by the models are compared with those of the study company and the revenues generated by various policies are estimated. The analysis suggests that if the firm had made smaller mark-downs earlier in the sales season, it would have increased its revenues significantly. The results also indicate that model-based pricing schemes can potentially increase revenue by approximately 4 per cent.

A Decision-Support System that Helps Retailers Decide Order Quantities and Markdowns for Fashion Goods

We developed MARK, a stochastic dynamic-programming model-based decision-support system, specifically to help retail-store buyers of fashion goods decide on optimal merchandise order quantities and markdown prices. We implemented MARK as an interactive software program that runs on users' personal computers and can be integrated with the retailers' point-of-sale (POS) and other information systems. As we show in an actual-case illustration, MARK improved profitability and managers' understanding of the decision problems. MARK also provides valuable insights into the interplay between order-quantity and dynamic-pricing decisions. For example, higher markdown percentages do not necessarily mean lower profits.

A Decision-Support System that Helps Retailers Decide Order Quantities and Markdowns for Fashion Goods

We developed MARK, a stochastic dynamic-programming model-based decision-support system, specifically to help retail-store buyers of fashion goods decide on optimal merchandise order quantities and markdown prices. We implemented MARK as an interactive software program that runs on users' personal computers and can be integrated with the retailers' point-of-sale (POS) and other information systems. As we show in an actual-case illustration, MARK improved profitability and managers' understanding of the decision problems. MARK also provides valuable insights into the interplay between order-quantity and dynamic-pricing decisions. For example, higher markdown percentages do not necessarily mean lower profits.

Markdown Pricing and Cattle Supply in the Beef Packing Industry

AbstractWe determine the effect of anticipated and unanticipated cattle supply on the departure of fed cattle price from cattle's marginal value product. Results indicate fed cattle were priced significantly below their marginal value during 31 of the 59 quarters between 1972II and 1986IV. When unanticipated supply shocks are small, markdown behavior is consistent with the hypothesis that packers follow an average processing cost (APC) pricing rule. One implication of our results is that reducing industry concentration is not likely to lead to changes in cattle prices predicted by SCP‐based studies of the industry.

Why Are Products Sold on Sale?: Explanations of Pricing Regularities

This paper reports on interesting changes in markdown pricing practices over time and differences in the pricing within a product line. The price discrimination and the uncertainty hypotheses appear to better explain the data than the peak load hypothesis. Fashion has become more important over time and appears to explain the greater seasonal variation in retail apparel prices in recent years. Differences in uncertainty also explains differences in the pricing of different types of men's dress shirts.